{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sun Jun  4 14:50:41 2023       \n",
      "+---------------------------------------------------------------------------------------+\n",
      "| NVIDIA-SMI 530.51.01              Driver Version: 532.03       CUDA Version: 12.1     |\n",
      "|-----------------------------------------+----------------------+----------------------+\n",
      "| GPU  Name                  Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n",
      "| Fan  Temp  Perf            Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n",
      "|                                         |                      |               MIG M. |\n",
      "|=========================================+======================+======================|\n",
      "|   0  NVIDIA GeForce RTX 3090         On | 00000000:09:00.0  On |                  N/A |\n",
      "| 97%   34C    P8               39W / 350W|    592MiB / 24576MiB |     14%      Default |\n",
      "|                                         |                      |                  N/A |\n",
      "+-----------------------------------------+----------------------+----------------------+\n",
      "                                                                                         \n",
      "+---------------------------------------------------------------------------------------+\n",
      "| Processes:                                                                            |\n",
      "|  GPU   GI   CI        PID   Type   Process name                            GPU Memory |\n",
      "|        ID   ID                                                             Usage      |\n",
      "|=======================================================================================|\n",
      "|  No running processes found                                                           |\n",
      "+---------------------------------------------------------------------------------------+\n"
     ]
    }
   ],
   "source": [
    "!nvidia-smi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "from torch import nn\n",
    "import torch.nn.functional as F\n",
    "from torch.utils.data import DataLoader\n",
    "from torch.utils.data import Dataset\n",
    "from torchvision import datasets, transforms\n",
    "from PIL import Image\n",
    "import pandas as pd\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "use_cuda = torch.cuda.is_available()\n",
    "device = torch.device(\"cuda\" if use_cuda else \"cpu\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Flatten(nn.Module):\n",
    "    def forward(self, x): return x.view(x.size(0), -1)\n",
    "\n",
    "class Net(nn.Sequential):\n",
    "    def __init__(self, i):\n",
    "        super().__init__(\n",
    "            nn.Conv2d(1, 32, 3, 1), nn.ReLU(),\n",
    "            *[layer for _ in range(i) for layer in [nn.Conv2d(32, 32, 1, 1), nn.ReLU()]],\n",
    "            nn.Conv2d(32, 64, 3, 1), nn.MaxPool2d(2), nn.Dropout(0.25),\n",
    "            Flatten(), nn.Linear(9216, 128), nn.ReLU(), nn.Dropout(0.5),\n",
    "            nn.Linear(128, 10), nn.LogSoftmax(dim=1) )\n",
    "\n",
    "def train(model, device, train_loader, optimizer, epoch):\n",
    "    model.train()\n",
    "    losses = []\n",
    "    for batch_idx, (data, target) in enumerate(train_loader):\n",
    "        data, target = data.to(device), target.to(device)\n",
    "        optimizer.zero_grad()\n",
    "        output = model(data)\n",
    "        loss = F.nll_loss(output, target)\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "        # if batch_idx % 100 == 0:\n",
    "        #     print('Train Epoch: {} [{}/{} ({:.0f}%)]\\tLoss: {:.6f}'.format(\n",
    "        #         epoch, batch_idx*len(data), len(train_loader.dataset),\n",
    "        #         100. * batch_idx/len(train_loader), loss.item()))\n",
    "        losses.append(loss.item())\n",
    "    return sum(losses)/len(losses)\n",
    "\n",
    "from sklearn.metrics import recall_score\n",
    "\n",
    "def test(model, device, test_loader):\n",
    "    model.eval()\n",
    "    test_loss = 0\n",
    "    all_preds = []\n",
    "    all_targets = []\n",
    "    \n",
    "    with torch.no_grad():\n",
    "        for data, target in test_loader:\n",
    "            data, target = data.to(device), target.to(device)\n",
    "            output = model(data)\n",
    "            test_loss += F.nll_loss(output, target, reduction='sum').item()\n",
    "            pred = output.argmax(dim=1, keepdim=True)\n",
    "            \n",
    "            # Store predictions and targets for recall calculation\n",
    "            all_preds.extend(pred.cpu().numpy())\n",
    "            all_targets.extend(target.cpu().numpy())\n",
    "    \n",
    "    recalls = recall_score(all_targets, all_preds, average=None)  # compute recall for each class\n",
    "\n",
    "    # print('\\nTest set: Average loss: {:.4f}, Recall: {:.2f}\\n'.format(\n",
    "    #     test_loss/len(test_loader.dataset), class_recall))\n",
    "\n",
    "    return sum(recalls)/len(recalls)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "class MyDataset(Dataset):\n",
    "    def __init__(self, data_dir, transforms=None):\n",
    "        self.data_dir = data_dir\n",
    "        self.data_info = self.get_img_info(data_dir)\n",
    "        self.transforms = transforms\n",
    "\n",
    "    def __getitem__(self, item):\n",
    "        path_img, label = self.data_info.iloc[item][1:3]\n",
    "        label = int(label)\n",
    "        path_img = os.path.join(self.data_dir, path_img)\n",
    "        image = Image.open(path_img).convert('RGB') # Gray scale is enough for logic interpretation\n",
    "        # 使用定义好的transforms，对数据进行处理\n",
    "        if self.transforms is not None:\n",
    "            image = self.transforms(image)\n",
    "\n",
    "        return image, label\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.data_info)\n",
    "    \n",
    "    def get_img_info(self, data_dir):\n",
    "        path_dir = os.path.join(data_dir, 'label.csv')\n",
    "        return pd.read_csv(path_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset_folder = \"dataset03\"\n",
    "exp_name = f\"{dataset_folder}_ablation_study_2_ref\"\n",
    "\n",
    "if not os.path.exists(f'./models/{exp_name}'):\n",
    "    os.mkdir(f'./models/{exp_name}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "kwargs = {'num_workers': 16}\n",
    "batch_size=256\n",
    "\n",
    "InDL = False\n",
    "if InDL:\n",
    "    transform = transforms.Compose(\n",
    "        [transforms.ToTensor(), transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))]) \n",
    "\n",
    "    trainset = MyDataset(f\"data/train/{dataset_folder}\", transform)\n",
    "    testset = MyDataset(f\"data/test/{dataset_folder}\", transform)\n",
    "else:\n",
    "    transform=transforms.Compose(\n",
    "        [transforms.ToTensor(),transforms.Normalize((0.1307,), (0.3081,))])\n",
    "\n",
    "    trainset = datasets.MNIST(root='data/mnist', train=True, download=True, transform=transform)\n",
    "    testset = datasets.MNIST(root='data/mnist', train=False, download=True, transform=transform)\n",
    "    \n",
    "    # trainset = datasets.CIFAR10(root='data/cifar10', train=True, download=True, transform=transform)\n",
    "    # testset = datasets.CIFAR10(root='data/cifar10', train=False, download=True, transform=transform)\n",
    "    \n",
    "\n",
    "train_loader = torch.utils.data.DataLoader(trainset, batch_size=batch_size, shuffle=True, **kwargs)\n",
    "test_loader = torch.utils.data.DataLoader(testset, batch_size=batch_size, shuffle=True, **kwargs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 100/100 [04:39<00:00,  2.80s/it]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 100/100 [04:49<00:00,  2.90s/it]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 100/100 [05:01<00:00,  3.01s/it]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 100/100 [05:06<00:00,  3.07s/it]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 100/100 [05:23<00:00,  3.24s/it]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 100/100 [05:57<00:00,  3.58s/it]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 100/100 [05:56<00:00,  3.57s/it]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 100/100 [06:08<00:00,  3.68s/it]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 100/100 [06:18<00:00,  3.79s/it]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 100/100 [06:29<00:00,  3.90s/it]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from tqdm import tqdm\n",
    "\n",
    "epochs, lr = 100, 1e-4\n",
    "\n",
    "for i in range(10):\n",
    "    df = pd.DataFrame(columns=['Loss', 'Recall'])\n",
    "    \n",
    "    model_name = f\"{i}-net\"\n",
    "    if InDL:\n",
    "        model_name = f\"{model_name}-InDL\"\n",
    "    else:\n",
    "        model_name = f\"{model_name}-MNIST\"\n",
    "\n",
    "    model = Net(i).to(device)\n",
    "    optimizer = torch.optim.AdamW(model.parameters(), lr=lr)\n",
    "    \n",
    "    model_path = f'./models/{exp_name}/{model_name}.pt'\n",
    "    history_path = f'./models/{exp_name}/{model_name}_history.csv'\n",
    "\n",
    "    if os.path.exists(history_path):\n",
    "        df = pd.read_csv(history_path)\n",
    "    else:\n",
    "        previous_best_recall = 0\n",
    "        for epoch in tqdm(range(1, epochs+1)):\n",
    "            loss = train(model, device, train_loader, optimizer, epoch)\n",
    "            recall = test(model, device, test_loader)\n",
    "            \n",
    "            df.loc[len(df)] = [loss, recall]\n",
    "            \n",
    "            if recall > previous_best_recall:\n",
    "                previous_best_recall = recall\n",
    "                torch.save(model.state_dict(), model_path)\n",
    "                \n",
    "        df.to_csv(history_path, index=False)\n",
    "\n",
    "    # Assuming df is your DataFrame and it has columns 'Loss' and 'Class 0 Recall'\n",
    "\n",
    "    fig, ax1 = plt.subplots()\n",
    "\n",
    "    # Plot Loss\n",
    "    sns.lineplot(data=df, x=df.index, y='Loss', ax=ax1, color='blue')\n",
    "    ax1.set_ylabel('Loss', color='blue')\n",
    "    ax1.tick_params(axis='y', labelcolor='blue')\n",
    "\n",
    "    # Create a second y-axis and plot Recall on it\n",
    "    ax2 = ax1.twinx()\n",
    "    sns.lineplot(data=df, x=df.index, y='Recall', ax=ax2, color='red')\n",
    "    ax2.set_ylabel('Recall', color='red')\n",
    "    ax2.tick_params(axis='y', labelcolor='red')\n",
    "    \n",
    "    ax1.set_xlabel('Epochs')\n",
    "\n",
    "    plt.show()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0-net-MNIST\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.99      1.00      0.99       980\n",
      "           1       0.99      1.00      1.00      1135\n",
      "           2       0.99      0.99      0.99      1032\n",
      "           3       0.99      0.99      0.99      1010\n",
      "           4       0.99      0.99      0.99       982\n",
      "           5       0.99      0.99      0.99       892\n",
      "           6       0.99      0.99      0.99       958\n",
      "           7       0.98      0.99      0.99      1028\n",
      "           8       0.99      0.99      0.99       974\n",
      "           9       0.99      0.98      0.99      1009\n",
      "\n",
      "    accuracy                           0.99     10000\n",
      "   macro avg       0.99      0.99      0.99     10000\n",
      "weighted avg       0.99      0.99      0.99     10000\n",
      "\n",
      "1-net-MNIST\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.99      1.00      0.99       980\n",
      "           1       0.99      1.00      1.00      1135\n",
      "           2       0.99      1.00      0.99      1032\n",
      "           3       0.99      1.00      0.99      1010\n",
      "           4       0.99      0.99      0.99       982\n",
      "           5       0.99      0.99      0.99       892\n",
      "           6       0.99      0.99      0.99       958\n",
      "           7       0.99      0.99      0.99      1028\n",
      "           8       1.00      0.98      0.99       974\n",
      "           9       0.99      0.99      0.99      1009\n",
      "\n",
      "    accuracy                           0.99     10000\n",
      "   macro avg       0.99      0.99      0.99     10000\n",
      "weighted avg       0.99      0.99      0.99     10000\n",
      "\n",
      "2-net-MNIST\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.98      1.00      0.99       980\n",
      "           1       1.00      0.99      1.00      1135\n",
      "           2       0.99      0.99      0.99      1032\n",
      "           3       0.99      1.00      0.99      1010\n",
      "           4       0.99      0.99      0.99       982\n",
      "           5       0.99      0.99      0.99       892\n",
      "           6       1.00      0.99      0.99       958\n",
      "           7       0.99      0.99      0.99      1028\n",
      "           8       0.99      0.99      0.99       974\n",
      "           9       0.99      0.98      0.99      1009\n",
      "\n",
      "    accuracy                           0.99     10000\n",
      "   macro avg       0.99      0.99      0.99     10000\n",
      "weighted avg       0.99      0.99      0.99     10000\n",
      "\n",
      "3-net-MNIST\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.98      1.00      0.99       980\n",
      "           1       0.99      1.00      1.00      1135\n",
      "           2       0.99      0.99      0.99      1032\n",
      "           3       1.00      0.99      0.99      1010\n",
      "           4       0.99      1.00      1.00       982\n",
      "           5       0.99      0.99      0.99       892\n",
      "           6       1.00      0.99      0.99       958\n",
      "           7       0.98      0.99      0.99      1028\n",
      "           8       1.00      0.99      0.99       974\n",
      "           9       0.99      0.99      0.99      1009\n",
      "\n",
      "    accuracy                           0.99     10000\n",
      "   macro avg       0.99      0.99      0.99     10000\n",
      "weighted avg       0.99      0.99      0.99     10000\n",
      "\n",
      "4-net-MNIST\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.99      0.99      0.99       980\n",
      "           1       1.00      0.99      0.99      1135\n",
      "           2       0.99      0.99      0.99      1032\n",
      "           3       0.99      0.99      0.99      1010\n",
      "           4       0.99      0.99      0.99       982\n",
      "           5       0.99      0.99      0.99       892\n",
      "           6       0.99      0.99      0.99       958\n",
      "           7       0.99      0.99      0.99      1028\n",
      "           8       0.99      0.99      0.99       974\n",
      "           9       0.99      0.98      0.98      1009\n",
      "\n",
      "    accuracy                           0.99     10000\n",
      "   macro avg       0.99      0.99      0.99     10000\n",
      "weighted avg       0.99      0.99      0.99     10000\n",
      "\n",
      "5-net-MNIST\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.99      0.99      0.99       980\n",
      "           1       0.99      1.00      0.99      1135\n",
      "           2       0.99      0.99      0.99      1032\n",
      "           3       0.99      0.99      0.99      1010\n",
      "           4       0.99      0.99      0.99       982\n",
      "           5       0.99      0.99      0.99       892\n",
      "           6       0.99      0.99      0.99       958\n",
      "           7       0.98      0.99      0.99      1028\n",
      "           8       0.99      0.99      0.99       974\n",
      "           9       0.99      0.98      0.99      1009\n",
      "\n",
      "    accuracy                           0.99     10000\n",
      "   macro avg       0.99      0.99      0.99     10000\n",
      "weighted avg       0.99      0.99      0.99     10000\n",
      "\n",
      "6-net-MNIST\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.99      0.99      0.99       980\n",
      "           1       1.00      0.99      0.99      1135\n",
      "           2       0.98      0.99      0.99      1032\n",
      "           3       0.98      0.99      0.99      1010\n",
      "           4       0.99      0.99      0.99       982\n",
      "           5       0.99      0.99      0.99       892\n",
      "           6       0.99      0.99      0.99       958\n",
      "           7       0.99      0.99      0.99      1028\n",
      "           8       0.99      0.99      0.99       974\n",
      "           9       0.99      0.99      0.99      1009\n",
      "\n",
      "    accuracy                           0.99     10000\n",
      "   macro avg       0.99      0.99      0.99     10000\n",
      "weighted avg       0.99      0.99      0.99     10000\n",
      "\n",
      "7-net-MNIST\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.99      0.99      0.99       980\n",
      "           1       0.99      0.99      0.99      1135\n",
      "           2       0.98      0.99      0.99      1032\n",
      "           3       0.99      0.99      0.99      1010\n",
      "           4       0.99      0.99      0.99       982\n",
      "           5       0.99      0.99      0.99       892\n",
      "           6       0.99      0.99      0.99       958\n",
      "           7       0.98      0.99      0.99      1028\n",
      "           8       0.99      0.99      0.99       974\n",
      "           9       0.99      0.98      0.98      1009\n",
      "\n",
      "    accuracy                           0.99     10000\n",
      "   macro avg       0.99      0.99      0.99     10000\n",
      "weighted avg       0.99      0.99      0.99     10000\n",
      "\n",
      "8-net-MNIST\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.99      0.99      0.99       980\n",
      "           1       0.99      0.99      0.99      1135\n",
      "           2       0.98      0.99      0.99      1032\n",
      "           3       0.99      1.00      0.99      1010\n",
      "           4       0.99      0.99      0.99       982\n",
      "           5       0.99      0.99      0.99       892\n",
      "           6       0.99      0.99      0.99       958\n",
      "           7       0.99      0.99      0.99      1028\n",
      "           8       0.99      0.98      0.99       974\n",
      "           9       0.99      0.98      0.99      1009\n",
      "\n",
      "    accuracy                           0.99     10000\n",
      "   macro avg       0.99      0.99      0.99     10000\n",
      "weighted avg       0.99      0.99      0.99     10000\n",
      "\n",
      "9-net-MNIST\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.98      0.99      0.99       980\n",
      "           1       0.99      0.99      0.99      1135\n",
      "           2       0.98      0.99      0.98      1032\n",
      "           3       0.99      0.99      0.99      1010\n",
      "           4       0.99      0.99      0.99       982\n",
      "           5       0.99      0.99      0.99       892\n",
      "           6       0.99      0.99      0.99       958\n",
      "           7       0.98      0.99      0.99      1028\n",
      "           8       0.99      0.99      0.99       974\n",
      "           9       0.99      0.98      0.98      1009\n",
      "\n",
      "    accuracy                           0.99     10000\n",
      "   macro avg       0.99      0.99      0.99     10000\n",
      "weighted avg       0.99      0.99      0.99     10000\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import classification_report\n",
    "\n",
    "def evaluate_model(model, dataloader, device):\n",
    "    model.eval()  # set the model to evaluation mode\n",
    "    \n",
    "    all_predictions = []\n",
    "    all_labels = []\n",
    "    \n",
    "    with torch.no_grad():  # don't calculate gradients\n",
    "        for inputs, labels in test_loader:\n",
    "            inputs = inputs.to(device)\n",
    "            labels = labels.to(device)\n",
    "            \n",
    "            outputs = model(inputs)\n",
    "            _, predictions = torch.max(outputs, 1)\n",
    "            \n",
    "            all_predictions.extend(predictions.cpu().numpy())\n",
    "            all_labels.extend(labels.cpu().numpy())\n",
    "    \n",
    "    print(classification_report(all_labels, all_predictions))\n",
    "\n",
    "for i in range(10):\n",
    "    model_name = f\"{i}-net\"\n",
    "    if InDL:\n",
    "        model_name = f\"{model_name}-InDL\"\n",
    "    else:\n",
    "        model_name = f\"{model_name}-MNIST\"\n",
    "        \n",
    "    if not os.path.exists(f\"models/{exp_name}/{model_name}.pt\"):\n",
    "        continue\n",
    "    state_dict = torch.load(f\"models/{exp_name}/{model_name}.pt\")\n",
    "    model = Net(i).to(device)\n",
    "    model.load_state_dict(state_dict)\n",
    "    \n",
    "    print(model_name)\n",
    "\n",
    "    # Assuming you have a model, dataloader and device (CPU or CUDA) defined\n",
    "    evaluate_model(model, test_loader, device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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